2,447 research outputs found

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    Predicting Safety Benefits of Automated Emergency Braking at Intersections - Virtual simulations based on real-world accident data

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    Introduction: Intersections are a global traffic safety concern. In the United States, around half of all fatal road traffic accidents take place at intersections or were related to them. In the European Union, about one fifth of road traffic fatalities occur at intersections.Intersection Automated Emergency Braking (AEB) seems to be a promising technology with which to address intersection accidents, as information retrieval by on-board sensing is operational on its own, and, in critical situations, braking is initiated independent of driver reaction. This is not the case for Vehicle-to-Everything (V2X) communication, which requires all conflict-involved vehicles to be equipped with this technology and drivers to respond to an initiated warning. The objective of this thesis is to evaluate the effectiveness of a theoretical Intersection AEB system in avoiding accidents and mitigating injuries. As it will take several decades for a new safety technology to penetrate the vehicle fleet and full coverage of all vehicles may never be achieved, the technology benefit is here analyzed as a function of market penetration. Finally, this research assesses whether a set of test scenarios can be derived without compromising the variance of real-world accidents.Methods: Data from the United States National Automotive Sampling System / General Estimates System and the Fatality Analysis Reporting System was used to compare the capacity of on-board sensing and V2X communication to save lives. To investigate Intersection AEB in detail, the German In-Depth Accident Study (GIDAS) data and the related Pre-Crash Matrix (PCM) were utilized to re-simulate accidents with and without Intersection AEB using different parameter settings of technical aspects and driver comfort boundaries. Machine learning techniques were used to identify opportunities for data clustering.Result: On-board sensing has a substantially higher capability to save lives than V2X communication during the period before full market penetration of both is reached. The analysis of GIDAS and PCM data indicate that about two thirds of left-turn across path accidents with oncoming traffic (LTAP/OD) and about 80 percent of straight crossing path (SCP) accidents can be avoid by an idealized Intersection AEB. Moderate to fatal injuries could be avoided to an even higher extent. Key parameters impacting effectiveness are vehicle speed and potential path choice; to increase effectiveness, these should be limited and narrowed down, respectively.Conclusion and Limitations: Intersection AEB is effective in reducing LTAP/OD and SCP accidents and mitigating injuries However, intersection accidents are highly diverse and accurate performance evaluation requires taking variations into account. The simulations were conducted using ideal sensing without processing delays and an ideal coefficient of friction estimation

    Modeling Lead-vehicle Kinematics For Rear-end Crash Scenario Generation

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    The use of virtual safety assessment as the primary method for evaluating vehicle safety technologies has emphasized the importance of crash scenario generation. One of the most common crash types is the rear-end crash, which involves a lead vehicle and a following vehicle. Most studies have focused on the following vehicle, assuming that the lead vehicle maintains a constant acceleration/deceleration before the crash. However, there is no evidence for this premise in the literature. This study aims to address this knowledge gap by thoroughly analyzing and modeling the lead vehicle's behavior as a first step in generating rear-end crash scenarios. Accordingly, the study employed a piecewise linear model to parameterize the speed profiles of lead vehicles, utilizing two rear-end pre-crash/near-crash datasets. These datasets were merged and categorized into multiple sub-datasets; for each one, a multivariate distribution was constructed to represent the corresponding parameters. Subsequently, a synthetic dataset was generated using these distribution models and validated by comparison with the original combined dataset. The results highlight diverse lead-vehicle speed patterns, indicating that a more accurate model, such as the proposed piecewise linear model, is required instead of the conventional constant acceleration/deceleration model. Crashes generated with the proposed models accurately match crash data across the full severity range, surpassing existing lead-vehicle kinematics models in both severity range and accuracy. By providing more realistic speed profiles for the lead vehicle, the model developed in the study contributes to creating realistic rear-end crash scenarios and reconstructing real-life crashes

    Evoked potentials and behavioral performance during different states of brain arousal

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    Additional file 4. Paired sample t-tests for comparisons of EPs and behavioral performance between EEG-vigilance (sub-)stages

    The influence of nitrogen oxides on the activation of bromide and chloride in salt aerosol

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    Abstract. Experiments on salt aerosol with different salt contents were performed in a Teflon chamber under tropospheric light conditions with various initial contents of nitrogen oxides (NOx = NO + NO2). A strong activation of halogens was found at high NOx mixing ratios, even in samples with lower bromide contents such as road salts. The ozone depletion by reactive halogen species released from the aerosol, was found to be a function of the initial NOx mixing ratio. Besides bromine, large amounts of chlorine have been released in our smog chamber. Time profiles of the halogen species Cl2, Br2, ClNO2, BrNO2 and BrO, ClO, OClO and Cl atoms were simultaneously measured by various techniques (chemical ionization mass spectrometry, differential optical absorption spectrometry coupled with a multi-reflection cell and gas chromatography of hydrocarbon tracers for Cl and OH, employing cryogenic preconcentration and flame ionization detection). Measurements are compared to calculations by the CAABA/MECCA 0-D box model, which was adapted to the chamber conditions and took the aerosol liquid water content and composition into account. The model results agree reasonably with the observations and provide important information about the prerequisites for halogen release, such as the time profiles of the aerosol bromide and chloride contents as well as the aerosol pH.</jats:p

    The Big Five Personality Traits and Brain Arousal in the Resting State

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    Based on Eysenck’s biopsychological trait theory, brain arousal has long been considered to explain individual differences in human personality. Yet, results from empirical studies remained inconclusive. However, most published results have been derived from small samples and, despite inherent limitations, EEG alpha power has usually served as an exclusive indicator for brain arousal. To overcome these problems, we here selected N = 468 individuals of the LIFE-Adult cohort and investigated the associations between the Big Five personality traits and brain arousal by using the validated EEG- and EOG-based analysis tool VIGALL. Our analyses revealed that participants who reported higher levels of extraversion and openness to experience, respectively, exhibited lower levels of brain arousal in the resting state. Bayesian and frequentist analysis results were especially convincing for openness to experience. Among the lower-order personality traits, we obtained the strongest evidence for neuroticism facet ‘impulsivity’ and reduced brain arousal. In line with this, both impulsivity and openness have previously been conceptualized as aspects of extraversion. We regard our findings as well in line with the postulations of Eysenck and consistent with the recently proposed ‘arousal regulation model’. Our results also agree with meta-analytically derived effect sizes in the field of individual differences research, highlighting the need for large (collaborative) studies.Peer Reviewe

    Time course and mechanisms of endo-epicardial electrical dissociation during atrial fibrillation in the goat

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    Aims This study aims to determine the degree and mechanisms of endo-epicardial dissociation of electrical activity during atrial fibrillation (AF) and endo-epicardial differences in atrial electrophysiology at different stages of atrial remodelling. Methods and results Simultaneous high-density endo-epicardial mapping of AF was performed on left atrial free walls of goats with acute AF, after 3 weeks, and after 6 months of AF (all n = 7). Endo-epicardial activation time differences and differences in the direction of conduction vectors were calculated, endocardial and epicardial effective refractory periods (ERP) were determined, and fractionation of electrograms was quantified. Histograms of endo-epicardial activation time differences and differences in the direction of conduction vectors revealed two distinct populations, i.e. dissociated and non-dissociated activity. Dyssynchronous activity (dissociated in time) increased from 17 ± 7% during acute AF to 39 ± 17% after 3 weeks, and 68 ± 13% after 6 months of AF. Dissociation was more pronounced in thicker parts of the atrial wall (thick: 49.3 ± 21.4%, thin: 42.2 ± 19.0%, P < 0.05). At baseline, endocardial ERPs were longer when compared with epicardial ERPs (ΔERP, 21.8 ± 18 ms; P < 0.001). This difference was absent after 6 months of AF. The percentage of fractionated electrograms during rapid pacing increased from 9.4 ± 1.9% (baseline) to 18.6 ± 0.6% (6 months). Conclusion During AF, pronounced dissociation of electrical activity occurs between the epicardial layer and the endocardial bundle network. The increase in dissociation is due to owing to progressive uncoupling between the epicardial layer and the endocardial bundles and correlates with increasing stability and complexity of the AF substrat
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